Electronic messaging, through mechanisms such as E-mail, is an important method of communication. For instance, E-mail messaging enables global communication at negligible incremental cost and has contributed to the emergence of organizations that are distributed world-wide, allowing people to communicate across space and time. While a common application of electronic messaging is one of communication, it is now used for additional functions such as task management, social networking, personal archiving, and file transfer, to name a few such functions. Because of its popularity, users are faced with rising volumes of electronic messages. Large amounts of information need to be processed and organized. As such, without the aid of tools to assist with the organization of such large amounts of information, many users face electronic messaging overload.
A variety of approaches have been implemented to assist users with such large quantities of messages. For example, electronic message overload can be addressed at the level of the individual, by installing organization software, or at global level where email users worldwide adopt new standards of communication. There is also a time component: electronic messaging overload applies to both managing current electronic messages and handling past messages.
One way to handle electronic messages is to implement automatic foldering. That is, automatically moving user's electronic messages into folders based on either filtering rules or categorization rules. However, such schemes have drawbacks. The first is the reliance on the accuracy of classifiers on real-world data. While classifiers do exist that can classify electronic messages, implementation of highly accurate classifiers is a laborious task that requires extensive effort by highly skilled workers. Second, many users distrust automatic schemes in which electronic message disappear from the inbox, never to be seen again. Third, folders typically require seeding with example data so that the classifiers have instances from which to learn.
Although automatic foldering has its drawbacks, the classification of messages, into message categories, in principal, does help users to parse through messages. For example, having messages classified into just a few basic categories (e.g., promotions, social, updates, forums, travel, finance, and/or receipts) greatly assists a user (e.g., electronic message recipient) in determining which messages to review, and allows the recipient to review messages that are of a similar type at the same time (e.g., all personal messages at the same time, all promotional messages at the same time, etc.). Moreover, such classification helps to put similar messages in the same place, for ease of comparison. As such, message classification provides a more efficient, productive environment for recipients.
While highly accurate classifiers have been developed to correctly categorize messages, particularly in instances in which the universe of possible message classifications is limited to a small finite set, disagreement between the classification assigned to messages by automated classifiers and recipient opinion arises. In such instances, a user may manually recategorize the message, a process termed a message category correction event. For instance, consider the case in which an automated classifier classifies a given message as a promotion. The message is then delivered to the recipient of the message. The message recipient believes the message should be categorized under social. The message recipient uses a messaging application in which the category of messages is made known to the user to change the message category from promotion to social. Such message category correction events are typically done in order to provide the user with a means for more easily retrieving the message at a later date. For example, if messages are correctly categorized, the user can use a message category, with our without other search criteria, to retrieve the message.
Manual message category correction events, particularly in the context of receiving high volumes of message, and/or in the context of mobile devices with more limited user interface functionality, is not always satisfactory to the user and it has been observed that many users consequently do not recategorize messages that they perceive as being incorrectly categorized, or, perhaps, only recategorize a limited number of miscategorized messages rather than all miscategorized messages.
The above discussion highlights the need for improved tools for assisting users in identifying messages that are similar to a message that the user has selected. One such use case where this need exists is where the user has enacted a message category correction event on a specified message. Tools for semantically identifying similar messages are desired. More generally, tools that semantically identify messages that are similar to a message identified by a user for any purpose are needed.
The above identified technical problems are reduced or eliminated by the systems and methods disclosed herein.